A multisource approach for coastline mapping and identification of shoreline changes
Main Article Content
Abstract
Coastal dynamics are driven by phenomena of exogenous and endogenous nature. Characterizing factors that influence
their equilibrium and continuous monitoring are fundamental for effective environmental planning and
management of coastal areas. In order to monitor shoreline changes, we developed a methodology based on a
multisource and multitemporal approach. A database, related to the Ionian coast of Basilicata region (about 50
km), was implemented by using cartographic data (IGMI data), satellite imagery (SPOT-PX/XS, Landsat-TM,
Corona) and aerial data covering the period form 1949 to 2001. In particular, airborne data (1 m spatial resolution)
were acquired during a specific campaign we performed in 2000 and 2001. To obtain the best performance
from the available data, we applied a data fusion procedure on visible and thermal information. Different algorithms
were tested, such as band ratios and clustering for extracting the coastline. The best results from multispectral
data were obtained using a threshold algorithm we devised by exploiting the green, red and NIR bands,
whereas for panchromatic data we selected clustering as the more suitable method. Moreover, a GPS survey was
performed to evaluate the influence of tidal effects.
their equilibrium and continuous monitoring are fundamental for effective environmental planning and
management of coastal areas. In order to monitor shoreline changes, we developed a methodology based on a
multisource and multitemporal approach. A database, related to the Ionian coast of Basilicata region (about 50
km), was implemented by using cartographic data (IGMI data), satellite imagery (SPOT-PX/XS, Landsat-TM,
Corona) and aerial data covering the period form 1949 to 2001. In particular, airborne data (1 m spatial resolution)
were acquired during a specific campaign we performed in 2000 and 2001. To obtain the best performance
from the available data, we applied a data fusion procedure on visible and thermal information. Different algorithms
were tested, such as band ratios and clustering for extracting the coastline. The best results from multispectral
data were obtained using a threshold algorithm we devised by exploiting the green, red and NIR bands,
whereas for panchromatic data we selected clustering as the more suitable method. Moreover, a GPS survey was
performed to evaluate the influence of tidal effects.
Article Details
How to Cite
Guariglia, A., Buonamassa, A., Losurdo, A., Saladino, R., Trivigno, M. L., Zaccagnino, A. and Colangelo, A. (2006) “A multisource approach for coastline mapping and identification of shoreline changes”, Annals of Geophysics, 49(1). doi: 10.4401/ag-3155.
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